OPENNESS AND SPATIAL INEQUALITY

The spatial dimension of inequality is a key concern in the policy discourse, because it intersects and interacts with disparities between subnational entities and jurisdictions.

What exactly is spatial inequality? One way of linking standard interpersonal measure­ment of inequality to regional inequality is to decompose national inequality into a between-region and a within-region component. The share of national inequality accounted for by the between-region component—which would be zero were it not for the fact that average incomes differ across regions—is then a measure of regional inequality. The fraction of total inequality accounted for by variation in average income across regions depends, of course, on the number of regions. The larger the number of regions, the greater the inequality that can be attributed to regional difference in mean income. Estimates vary, but 15-20% of spatial inequality in total inequality is not unusual (see Kanbur, 2006).

An alternative, however, is to consider the disparities in regional mean incomes directly, not weighted by their population. Equal weights correspond to some dimen­sions of many constitutions, where key elements of political power are divided equally between constituent provinces or states (Kanbur and Venables, 2005). In the case of just two entities, then, this could be simply the ratio of the two means, for example. For more than two entities, other standard measures of dispersion can be used. Yet, other measures are sometimes used in the literature, attempting to capture regional “polarization.” How­ever, as Zhang and Kanbur (2001) argue, such measures may not make that much dif­ference in assessing trends.

Kanbur and Venables (2007) review the literature and provide other measures of the level of spatial disparities observed around the world. In particular, they highlight vari­ations in poverty and human development indicators. In Africa, in 6 out of the 12 coun­tries studied, the percentage of people below a poverty line constructed on the basis of information about households’ asset holdings is more than 50% greater in rural areas than in urban areas. The smallest rural-urban difference is 30%. Similarly, school enrollments, and the ratio of girls to boys enrolled, is much higher in urban than in rural areas. In Peru, the incidence of poverty in districts at sealevel was 46.1% in 1997, while for districts at an altitude greater than 3500 m above sea level it was 63.3%. In Indonesia in 1993, the rural poverty incidence was 46.5% in West Kalimantan, but only 10.7% in Yogyakarta.

However spatial inequality is measured, there are major differences in the literature on how much it should matter in policy design. One strand of the policy discourse can be characterized by the “balanced development” perspective, which holds that too much concentration of economic activity is inimical to equity and to efficiency. However, there is a contrary strand that is best expressed in the World Bank’s World Development Report on Economic Geography (World Bank, 2008, p. 73):

For decades, “spatially balanced growth" has been a mantra of policy makers in many developing countries. It was an obsession of planners in the former Soviet Union.... And it has been the objective of governments of various political hues in the Arab Republic of Egypt, Brazil, India, Indo­nesia, Mexico, Nigeria, the Russian Federation, South Africa, and other great developing nations. There has even been a strong commitment to spatially balanced development in the economic history of many developed countries.

This strong perspective against “balanced growth” in the conventional sense is important in light of the report’s own assessment of evolving economic forces, in particular global integration in the era of globalization:

Although the basic forces shaping the internal economic geography of developing countries are the same as those that earlier shaped the economic landscapes of today's developed countries, the magnitudes have changed.

World Bank (2008, p. 74)

The above perspective on openness and economic spatial disparity owes much to the burgeoning “new economic geography” literature that brings increasing returns to scale and agglomeration economies center stage in characterizing the development of an econ­omy. In the context of a closed economy with two sectors, one in which (“agriculture”) has conventional diminishing returns while the other (“manufacturing”) displays firm level costs that fall as the sector as a whole grows, equilibrium can have spatial concen­tration of economic activity even when there is no “natural” geographic differentiation between the regions.^{[346] [347] There is thus a distinction between spatial divergence caused by “first-nature geography,” natural variations in environmental endowment, and “second- nature geography” that arises out of the self-enforcing feedback loops of agglomeration 21}

economies.

What precisely is the impact of greater openness on spatial disparity when played through the forces of agglomeration economies? The World Bank (2008) quote above seems to suggest that spatial disparities will increase. However, the specific theory does not produce quite such a clear-cut answer. Different specifications, modeling different contexts, produce different answers.^[348] For example, it matters whether different regions have equal access to the international market. It also matters whether the opening up is only for trade or also for capital mobility. The theoretical ambiguity is emphasized in recent papers by Rodrlguez-Pose (2010) and Ottaviano (2009). Ottaviano (2009) sum­marizes the theoretical conclusions in a series of propositions as follows:

when regions have the same access to foreign markets, international trade liberalization fosters regional disparities and this effect is stronger the more important the foreign market and the more integrated the national market.

Given these theoretical ambiguities then, what is the evidence on openness and spatial inequality? KanburandVenables (2007) summarize the results ofa major project collating country case studies on the evolution of spatial inequality in the last quarter century. For 26 developing and transitioning countries, spatial inequality measures are available for at two or more points in time, so that we can get a sense of the time trends. The first and major empirical finding is that spatial inequalities have been rising in the last two to three decades.^[349]

The last three decades have also been the period of globalization. Is there then a link between openness on rising spatial inequality? The case studies reported in Kanbur and Venables (2007) seem to support the hypothesis that openness is associated with greater spatial inequality. Thus, Kanbur and Zhang (2005) establish dramatic increases in spatial inequality in China since the start of the reforms in 1978. Their econometric analysis attributes at least part of this increase to the measure of openness (the other factors that are statistically significant include the degree of decentralization). Rodrlguez-Pose and Sanchez-Reaza (2005) find greater regional polarization in Mexico comparing the periods before and after the North American Free Trade Agreement (NAFTA). Friedman (2005) identifies an indirect channel for Indonesia, in that openness leads to growth, but more remote areas benefit less from growth in terms of poverty reduction impact. Outside of the country studies reviewed in Kanbur and Venables (2007), Daumal (2008) finds that while for India openness contributes to greater inequality between Indian states, for Brazil the opposite is true.

A number of cross-country regression studies have also focused on the issue of the link between openness and spatial inequality. Barrios and Strobl (2009) regress within country regional inequality against trade openness, with other controls, for 15 European Union countries. They find a positive association between regional inequality and the trade to GDP ratio for a country. Milanovic (2005) considers the evolution of regional inequality over time in China, India, the United States, Indonesia, and Brazil over 1980—2000. He finds a significant causal relationship between measures of openness and measures of regional inequality. Rodrlguez-Pose and Gill (2006) analyze regional inequality similarly across country panels for the period 1970-2000. They find that it is the particular interac­tion of openness with the composition of trade that results in regional inequality impacts.

Perhaps the most recent and comprehensive cross-country study of regional inequal­ity and openness is by Rodrlguez-Pose (2010). It uses unbalanced panel data for 28 coun­tries over 1975-2005. Half of these countries are developed countries and the other half are developing or transition economies. The measure of regional inequality used is the Gini coefficient of regional GDP per capita. There is no simple association between openness and regional inequality in these data. However, this is before various controls are introduced, and the panel structure of the data is exploited with appropriate tech­niques. On the conditioning variables, use is made of the theory referred to earlier, so that “greater trade openness will have a more polarizing effect in countries characterized by (a) higher differences in foreign market accessibility among its regions and (b) where there is also a high degree of coincidence between the regional income distribution and accessibility to foreign markets” (Rodriguez-Pose, 2010, p. 13). Further, like Kanbur and Zhang’s (2005) work on China, it is hypothesized that the degree of decentralization will also matter for regional inequality.

The overall conclusion of the comprehensive and rigorous analysis by Rodriguez- Pose (2010) is striking:

By and large, countries in the developing world are characterized by a series of features that are likely to potentiate the spatially polarizing effects of greater openness to trade. Their higher existing levels of regional inequality, their greater degree of sector polarization, the fact that their wealthier regions often coincide with the key entry points to trade, and their weaker state all contribute to exacerbate regional disparities as trade with the external world increases.

Rodriguez-Pose (2010, p. 26)

Thus, structural differences in the country at the time of opening up tend to interact with the forces of openness, and in the recent experience at least, this has led to openness con­tributing to greater regional inequality. Of course, this leaves open the issue of whether this is not just the first-round effects of trade opening and whether it could it be weakened or offset by further geographical adjustments, namely, domestic migration of workers or capital, at a later stage. However, the inequality consequences in the short run will need to be addressed, and the policy implications of these findings will be discussed in a subsequent section.

20.7.